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Paper short abstract:

Over the last decade both the public discourse around the value of data - reflecting the economic imperative- as well as the implications of such logic in the increasingly data-driven healthcare sector, are highliting the need to account for a value theory of of data as commons.

Paper long abstract:

Over the last few years, the intrusion of the Big Tech in digital healthcare with AI technologies -data-driven decision making (Sharon, 2018) has accelerated the notions of individual "choice" and "personalised access" to healthcare (Mol, 2008), through the intensive collection and use of data. This turn corresponds to the logic of neoliberal economic imperative, which in the realm of data-driven services, is particularly manifested with dominating metaphors such as "data is the new oil" (Neelie Croes, 2011).

Academic scholarship (Birch, 2021; Thatcher, 2017; Taffer, 2021) has scrutinised the extractivist material relationships the data-oil associations signify. In this direction, "data (as) commons" and "Data as a relation" metaphors are developed both by scholars and activists, in order to account for alternative data-value conceptualisations (Viljoen, 2021; Purtova, 2017). This strand of discourse is accounting for data as common(s) or relationships via alternative data governance models (i.e. Data Trusts, Data cooperatives), yet it lacks an underpinning theory of how data come to be valued within socio-economic systems.

This paper argues that we cannot constitute "data commons" if we don't account for a value theory of the commons, and the latter cannot be done, if we don't provide an alternative understanding of data. This will be done by interviewing people from two companies, which utilise AI technologies for patient screenings, and for matching patients to new clinical trials. By exploring the market's understanding of health data, this paper accounts for the missing step, before we look into the alternative data-commons conceptualisations.